Senior Software Engineer, AI Transformation
New
Remote-first work environment within the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of software engineering experience
- Required Skills
- AWSGraphQLNode.jsPythonRubyTypeScriptGoRESTful APIsLLMLangChain
Requirements
- 8+ years of software engineering experience, ideally focused on infrastructure, developer tools, or internal platforms
- Strong proficiency in at least one backend programming language such as Python, Go, TypeScript/Node.js, or Ruby
- Hands-on experience working with LLM platforms or orchestration frameworks (e.g., AWS Bedrock, OpenAI, Anthropic, LangChain, LiteLLM, or similar)
- Experience designing and building backend services, APIs (REST/GraphQL), or event-driven systems at scale
- Proven experience integrating AI capabilities into real-world workflows, including tool-calling, agents, or multi-step orchestration systems
- Strong understanding of AWS cloud infrastructure and secure-by-design engineering practices
- Experience building internal tools such as chatops, CLIs, bots, or workflow automation systems
- Ability to collaborate cross-functionally and translate complex operational workflows into technical solutions
- Strong communication, documentation, and stakeholder management skills
Responsibilities
- Design and build AI-powered developer tools integrated into everyday engineering workflows such as IDEs, Slack, documentation systems, and observability platforms
- Develop and maintain backend services and infrastructure that support LLM-driven workflows, including tool-calling, orchestration, and agentic systems
- Implement and evolve AI inference pipelines using modern LLM platforms and frameworks
- Partner with engineering, product, and infrastructure teams to define AI-augmented software development lifecycle (SDLC) patterns
- Build internal chat-based and automation tools that safely orchestrate systems and services through agent-driven interfaces
- Instrument, monitor, and analyze AI usage, performance, cost, and reliability
- Develop reusable libraries, templates, and frameworks for consistent AI workflow adoption
- Collaborate with security and compliance teams to ensure safe handling of sensitive data
- Contribute to documentation, training materials, and enablement sessions
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